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Managing Data In Motion

Author: April Reeve
Publisher: Newnes
ISBN: 0123977916
Size: 43.52 MB
Format: PDF, ePub
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Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types Explains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"

Software Quality Software And Systems Quality In Distributed And Mobile Environments

Author: Dietmar Winkler
Publisher: Springer
ISBN: 3319132512
Size: 72.66 MB
Format: PDF, ePub, Docs
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This book constitutes the refereed proceedings of the scientific track of the 7th Software Quality Days Conference, SWQD 2015, held in Vienna, Austria, in January 2015. The SWQD conference offers a range of comprehensive and valuable information by presenting new ideas from the latest research papers, keynote speeches by renowned academics and industry leaders, professional lectures, exhibits, and tutorials. The four scientific full papers accepted for SWQD were each peer reviewed by three or more reviewers and selected out of 13 high-quality submissions. Further, four short papers were also presented and are included in this book. The papers are organized into topical sections on risk management and inspection, change impact analysis and systems testing, and software and systems architectures.

Proceedings Of The Fourth International Forum On Decision Sciences

Author: Xiang Li
Publisher: Springer
ISBN: 9811029202
Size: 18.66 MB
Format: PDF, ePub
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These conference proceedings focus on the topics of data-driven decision-making, stochastic decision-making, fuzzy decision-making and their applications in real-life problems. Beijing University of Chemical Technology organized IFDS2016, the 4th International Forum on Decision Sciences, with the theme “Data-Driven Decision-Making.” The proceedings collect 84 selected papers presenting cutting-edge modeling and solution methods and include numerous practical case studies, making it a valuable resource for students, researchers and practitioners working in the fields of decision science, operations research, management science and engineering.

Principles Of Data Integration

Author: AnHai Doan
Publisher: Elsevier
ISBN: 0123914795
Size: 22.78 MB
Format: PDF, Docs
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How do you approach answering queries when your data is stored in multiple databases that were designed independently by different people? This is first comprehensive book on data integration and is written by three of the most respected experts in the field. This book provides an extensive introduction to the theory and concepts underlying today's data integration techniques, with detailed, instruction for their application using concrete examples throughout to explain the concepts. Data integration is the problem of answering queries that span multiple data sources (e.g., databases, web pages). Data integration problems surface in multiple contexts, including enterprise information integration, query processing on the Web, coordination between government agencies and collaboration between scientists. In some cases, data integration is the key bottleneck to making progress in a field. The authors provide a working knowledge of data integration concepts and techniques, giving you the tools you need to develop a complete and concise package of algorithms and applications. Offers a range of data integration solutions enabling you to focus on what is most relevant to the problem at hand Enables you to build your own algorithms and implement your own data integration applications

Master Data Management In Practice

Author: Dalton Cervo
Publisher: John Wiley & Sons
ISBN: 0470910550
Size: 31.88 MB
Format: PDF, Kindle
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Dalton and Mark explain how MDM does much more than just bring data together-it provides a set of processes, services, and policies that bring people together in a cross-functional and collaborative approach to enterprise data management, where people, empowered by high quality data and enabled by technology, can optimize business processes for superior business performance."--Jim Harris, independent consultant, speaker, and freelance writer, as well as the Blogger-in-Chief at Ob

Data Mining Concepts And Techniques

Author: Jiawei Han
Publisher: Elsevier
ISBN: 9780123814807
Size: 12.64 MB
Format: PDF, Mobi
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Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Readings In Information Visualization

Author: Stuart K. Card
Publisher: Morgan Kaufmann
ISBN: 9781558605336
Size: 26.17 MB
Format: PDF, Docs
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This groundbreaking book defines the emerging field of information visualization and offers the first-ever collection of the classic papers of the discipline, with introductions and analytical discussions of each topic and paper. The authors' intention is to present papers that focus on the use of visualization to discover relationships, using interactive graphics to amplify thought. This book is intended for research professionals in academia and industry; new graduate students and professors who want to begin work in this burgeoning field; professionals involved in financial data analysis, statistics, and information design; scientific data managers; and professionals involved in medical, bioinformatics, and other areas. * Full-color reproduction throughout * Author power team - an exciting and timely collaboration between the field's pioneering, most-respected names * The only book on Information Visualization with the depth necessary for use as a text or as a reference for the information professional * Text includes the classic source papers as well as a collection of cutting edge work

The Profit Impact Of Business Intelligence

Author: Steve Williams
Publisher: Elsevier
ISBN: 9780080467764
Size: 65.73 MB
Format: PDF
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The Profit Impact of Business Intelligence presents an A-to-Z approach for getting the most business intelligence (BI) from a company's data assets or data warehouse. BI is not just a technology or methodology, it is a powerful new management approach that – when done right – can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it. When BI first came on the scene, it promised a lot but often failed to deliver. The missing element was the business-centric focus explained in this book. It shows how you can achieve the promise of BI by connecting it to your organization’s strategic goals, culture, and strengths while correcting your BI weaknesses. It provides a practical, process-oriented guide to achieve the full promise of BI; shows how world-class companies used BI to become leaders in their industries; helps senior business and IT executives understand the strategic impact of BI and how they can ensure a strong payoff from their BI investments; and identifies the most common mistakes organizations make in implementing BI. The book also includes a helpful glossary of BI terms; a BI readiness assessment for your organization; and Web links and extensive references for more information. A practical, process-oriented book that will help organizations realize the promise of BI Written by Nancy and Steve Williams, veteran consultants and instructors with hands-on, "in the trenches" experience in government and corporate business intelligence applications Will help senior business and IT executives understand the strategic impact of BI and how they can help ensure a strong payoff on BI investments

Big Data Analytics

Author: David Loshin
Publisher: Elsevier
ISBN: 0124186645
Size: 59.93 MB
Format: PDF
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Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem